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Record W2017109414 · doi:10.1002/pssc.200674269

Two‐dimensional simulation of type‐II InP/GaAsSb/InP double heterojunction bipolar transistors

2007· article· en· W2017109414 on OpenAlexafffund
N.G. Tao, Hongxu Liu, C. R. Bolognesi

Bibliographic record

VenuePhysica status solidi. C, Conferences and critical reviews/Physica status solidi. C, Current topics in solid state physics · 2007
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSemiconductor Quantum Structures and Devices
Canadian institutionsSimon Fraser University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBipolar junction transistorCommon emitterHeterojunctionHeterojunction bipolar transistorMaterials scienceOptoelectronicsBand gapDopingHeterostructure-emitter bipolar transistorSurface (topology)Base (topology)TransistorPhysicsVoltage

Abstract

fetched live from OpenAlex

Abstract Two‐dimensional (2D) numerical simulations of self‐aligned sub‐micron InP/GaAsSb double heterojunction bipolar transistors (DHBTs) were performed to investigate the effects of base band gap narrowing and surface recombination. Base energy band gaps of 0.72 eV and 0.67 eV for GaAs0.51Sb0.49 bases with doping levels of 5×1018 and 5×1019 cm–3 were extracted from the comparison between the measurement data and simulation results. We took into account the surface Fermi level pinning and introduced a surface state model for the emitter side wall and extrinsic base surface. To the best of our knowledge, a good match between measured and simulated InP/GaAsSb DHBTs characteristics, from low to high current densities has not been achieved prior to the present work. (© 2007 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.061
GPT teacher head0.379
Teacher spread0.318 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2007
Admission routes2
Has abstractyes

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